Genetic Algorithm Optimization based Control for Heat Integrated Distillation Column

Controlling nonlinear heat integrated distillation column (HIDiC) systems is notably challenging due to their complex dynamics and inherent nonlinearities. This study examines the effectiveness of genetic algorithm (GA) optimization in enhancing proportional-integral (PI) controller performance for HIDiC systems. A nonlinear mechanistic model of a HIDiC was adopted, with the GA applied to tune the PI controllers for optimal control performance. Control performance was tested under varying setpoints and feed composition disturbances. Simulation results demonstrate that the GA-tuned PI controller provides robust control performance, maintaining stability and high product purity even with significant disturbances. Initial oscillations due to feed composition disturbance are minimal and quickly settle down, confirming the controller's capability to achieve precise control and high separation performance.